Installation

Requirements

• Python 3.8+
• See requirements.txt for dependencies

Setup

1. Clone the repository
2. Create virtual environment (optional but recommended):

   python -m venv venv
   source venv/bin/activate  # On Windows: venv\Scripts\activate
   

Install dependencies: bash pip install -r requirements.txt

2. Project Structure

     ├── data/
     │ └── England.csv # Premier League match data
     ├── src/
     │ ├── data_loader.py # Data loading & preprocessing
     │ ├── clustering.py # K-Means clustering logic
     │ └── models.py # Random Forest models
     ├── config.py # Configuration parameters
     ├── main.py # Main execution script
     └── requirements.txt # Dependencies

Results

The analysis generates:

• Cluster visualizations (scatter plots, heatmaps)
• Model performance metrics (accuracy, precision, recall)
• JSON output with cluster statistics

Key Features

• 9,300+ matches analyzed (2000/01 season onwards)
• K-Means Clustering to identify match archetypes
• Random Forest models for goal prediction
• Comparative analysis vs baseline models

Contributing

Pull requests welcome!

License

MIT